Managing Distribution in Supply Chain Networks

Autores
Dondo, Rodolfo Gabriel; Mendez, Carlos Alberto; Cerda, Jaime
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
This paper presents a novel optimization approach to the short-term operational planning of multiechelon multiproduct transportation networks. Distribution activities commonly arising in real-world chemical supply chains involve the shipping of a number of commodities from factories to customers directly and/or via distribution centers and regional warehouses. To optimally manage such complex distribution systems, a more general vehicle routing problem in supply chain management (VRP-SCM) has been defined. The new VRP-SCM problem better resembles the logistics activities to be planned at multisite manufacturing firms by allowing multiple events at every location. In this way, two or more vehicles can visit a given location to perform pickup and/or delivery operations, and vehicle routes may include several stops at the same site, i.e., multiple tours per route. More important, the allocation of customers to suppliers and the quantities of products shipped from each source to a particular client are additional model decisions. Both the capacitated vehicle routing problem (VRP) and the pickup-and-delivery problem (PDP) can be regarded as particular instances of the new VRP-SCM. The proposed MILP mathematical formulation for the VRP-SCM problem relies on a continuous-time representation and applies the general precedence notion to model the sequencing constraints establishing the ordering of vehicle stops on every route. The approach provides a very detailed set of optimal vehicle routes and schedules to meet all product demands at minimum total transportation cost. Several examples involving up to 26 locations, four products, and six vehicles housed in four different depots have been solved to optimality in very short CPU times.
Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Materia
Supply Chain Networks
Distribution Operations
Vehicle Routing Problems
Routing And Scheduling
Mathematical Model
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/22347
Acceder
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network_name_str CONICET Digital (CONICET)
spelling Managing Distribution in Supply Chain NetworksDondo, Rodolfo GabrielMendez, Carlos AlbertoCerda, JaimeSupply Chain NetworksDistribution OperationsVehicle Routing ProblemsRouting And SchedulingMathematical Modelhttps://purl.org/becyt/ford/2.4https://purl.org/becyt/ford/2This paper presents a novel optimization approach to the short-term operational planning of multiechelon multiproduct transportation networks. Distribution activities commonly arising in real-world chemical supply chains involve the shipping of a number of commodities from factories to customers directly and/or via distribution centers and regional warehouses. To optimally manage such complex distribution systems, a more general vehicle routing problem in supply chain management (VRP-SCM) has been defined. The new VRP-SCM problem better resembles the logistics activities to be planned at multisite manufacturing firms by allowing multiple events at every location. In this way, two or more vehicles can visit a given location to perform pickup and/or delivery operations, and vehicle routes may include several stops at the same site, i.e., multiple tours per route. More important, the allocation of customers to suppliers and the quantities of products shipped from each source to a particular client are additional model decisions. Both the capacitated vehicle routing problem (VRP) and the pickup-and-delivery problem (PDP) can be regarded as particular instances of the new VRP-SCM. The proposed MILP mathematical formulation for the VRP-SCM problem relies on a continuous-time representation and applies the general precedence notion to model the sequencing constraints establishing the ordering of vehicle stops on every route. The approach provides a very detailed set of optimal vehicle routes and schedules to meet all product demands at minimum total transportation cost. Several examples involving up to 26 locations, four products, and six vehicles housed in four different depots have been solved to optimality in very short CPU times.Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaAmerican Chemical Society2009-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/22347Dondo, Rodolfo Gabriel; Mendez, Carlos Alberto; Cerda, Jaime; Managing Distribution in Supply Chain Networks; American Chemical Society; Industrial & Engineering Chemical Research; 48; 22; 12-2009; 9961-99780888-5885CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/http://pubs.acs.org/doi/abs/10.1021/ie900792sinfo:eu-repo/semantics/altIdentifier/doi/10.1021/ie900792sinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:43:06Zoai:ri.conicet.gov.ar:11336/22347instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 14:43:06.695CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Managing Distribution in Supply Chain Networks
title Managing Distribution in Supply Chain Networks
spellingShingle Managing Distribution in Supply Chain Networks
Dondo, Rodolfo Gabriel
Supply Chain Networks
Distribution Operations
Vehicle Routing Problems
Routing And Scheduling
Mathematical Model
title_short Managing Distribution in Supply Chain Networks
title_full Managing Distribution in Supply Chain Networks
title_fullStr Managing Distribution in Supply Chain Networks
title_full_unstemmed Managing Distribution in Supply Chain Networks
title_sort Managing Distribution in Supply Chain Networks
dc.creator.none.fl_str_mv Dondo, Rodolfo Gabriel
Mendez, Carlos Alberto
Cerda, Jaime
author Dondo, Rodolfo Gabriel
author_facet Dondo, Rodolfo Gabriel
Mendez, Carlos Alberto
Cerda, Jaime
author_role author
author2 Mendez, Carlos Alberto
Cerda, Jaime
author2_role author
author
dc.subject.none.fl_str_mv Supply Chain Networks
Distribution Operations
Vehicle Routing Problems
Routing And Scheduling
Mathematical Model
topic Supply Chain Networks
Distribution Operations
Vehicle Routing Problems
Routing And Scheduling
Mathematical Model
purl_subject.fl_str_mv https://purl.org/becyt/ford/2.4
https://purl.org/becyt/ford/2
dc.description.none.fl_txt_mv This paper presents a novel optimization approach to the short-term operational planning of multiechelon multiproduct transportation networks. Distribution activities commonly arising in real-world chemical supply chains involve the shipping of a number of commodities from factories to customers directly and/or via distribution centers and regional warehouses. To optimally manage such complex distribution systems, a more general vehicle routing problem in supply chain management (VRP-SCM) has been defined. The new VRP-SCM problem better resembles the logistics activities to be planned at multisite manufacturing firms by allowing multiple events at every location. In this way, two or more vehicles can visit a given location to perform pickup and/or delivery operations, and vehicle routes may include several stops at the same site, i.e., multiple tours per route. More important, the allocation of customers to suppliers and the quantities of products shipped from each source to a particular client are additional model decisions. Both the capacitated vehicle routing problem (VRP) and the pickup-and-delivery problem (PDP) can be regarded as particular instances of the new VRP-SCM. The proposed MILP mathematical formulation for the VRP-SCM problem relies on a continuous-time representation and applies the general precedence notion to model the sequencing constraints establishing the ordering of vehicle stops on every route. The approach provides a very detailed set of optimal vehicle routes and schedules to meet all product demands at minimum total transportation cost. Several examples involving up to 26 locations, four products, and six vehicles housed in four different depots have been solved to optimality in very short CPU times.
Fil: Dondo, Rodolfo Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
Fil: Cerda, Jaime. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentina
description This paper presents a novel optimization approach to the short-term operational planning of multiechelon multiproduct transportation networks. Distribution activities commonly arising in real-world chemical supply chains involve the shipping of a number of commodities from factories to customers directly and/or via distribution centers and regional warehouses. To optimally manage such complex distribution systems, a more general vehicle routing problem in supply chain management (VRP-SCM) has been defined. The new VRP-SCM problem better resembles the logistics activities to be planned at multisite manufacturing firms by allowing multiple events at every location. In this way, two or more vehicles can visit a given location to perform pickup and/or delivery operations, and vehicle routes may include several stops at the same site, i.e., multiple tours per route. More important, the allocation of customers to suppliers and the quantities of products shipped from each source to a particular client are additional model decisions. Both the capacitated vehicle routing problem (VRP) and the pickup-and-delivery problem (PDP) can be regarded as particular instances of the new VRP-SCM. The proposed MILP mathematical formulation for the VRP-SCM problem relies on a continuous-time representation and applies the general precedence notion to model the sequencing constraints establishing the ordering of vehicle stops on every route. The approach provides a very detailed set of optimal vehicle routes and schedules to meet all product demands at minimum total transportation cost. Several examples involving up to 26 locations, four products, and six vehicles housed in four different depots have been solved to optimality in very short CPU times.
publishDate 2009
dc.date.none.fl_str_mv 2009-12
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/22347
Dondo, Rodolfo Gabriel; Mendez, Carlos Alberto; Cerda, Jaime; Managing Distribution in Supply Chain Networks; American Chemical Society; Industrial & Engineering Chemical Research; 48; 22; 12-2009; 9961-9978
0888-5885
CONICET Digital
CONICET
url http://hdl.handle.net/11336/22347
identifier_str_mv Dondo, Rodolfo Gabriel; Mendez, Carlos Alberto; Cerda, Jaime; Managing Distribution in Supply Chain Networks; American Chemical Society; Industrial & Engineering Chemical Research; 48; 22; 12-2009; 9961-9978
0888-5885
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://pubs.acs.org/doi/abs/10.1021/ie900792s
info:eu-repo/semantics/altIdentifier/doi/10.1021/ie900792s
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Chemical Society
publisher.none.fl_str_mv American Chemical Society
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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